JGSED: An End-to-End Spectral Clustering Model for Joint Graph Construction, Spectral Embedding and Discretization-Reference-Cited by-同舟云学术

JGSED: An End-to-End Spectral Clustering Model for Joint Graph Construction, Spectral Embedding and Discretization

Published:2023-12 Issue:6 Volume:7 Page:1687-1701
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Peng Yong¹^ORCID,Huang Wenna¹,Kong Wanzeng¹^ORCID,Nie Feiping²^ORCID,Lu Bao-Liang³^ORCID

Affiliation:

1. School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China

2. School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi'an, China

3. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

Funder

Natural Science Foundation of Zhejiang Province

National Natural Science Foundation of China

Key Research and Development Project of Zhejiang Province

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computational Mathematics,Control and Optimization,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7433297/10325841/10049299.pdf?arnumber=10049299

Reference49 articles.

1. Spectral Clustering of Large-scale Data by Directly Solving Normalized Cut

2. Sparse Subspace Clustering for Stream Data

3. Parameter-free auto-weighted multiple graph learning: A framework for multiview clustering and semi-supervised classification;nie;Proc Int J Conf Artif Intell,0

4. Fuzzy graph clustering

5. Robust Subspace Clustering With Compressed Data

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